Yolov8如何在训练意外中断后接续训练 |
您所在的位置：网站首页 › 终端停止训练怎么办 › Yolov8如何在训练意外中断后接续训练 |
|
0. 2023年11月更新
请使用第四节的新方法，不需要修改代码，更加简单。 1.错误尝试在训练YOLOv8的时候，因为开太多其他程序，导致在100多次的时候崩溃，查询网上相关知识如何接着训练，在yolo5中把resume改成True就可以。 在yolov8中也这样尝试，将ultralytics/yolo/cfg/default.yaml中的resume改成True发现并没有作用，感觉yolov8代码还是有很多bug 2.成功的方法 2.1 ultralytics/yolo/engine/model.py打开ultralytics/yolo/engine/model.py代码，找到train方法，如下 将self.trainer.model = self.model注释掉 def train(self, **kwargs): """ Trains the model on a given dataset. Args: **kwargs (Any): Any number of arguments representing the training configuration. """ overrides = self.overrides.copy() overrides.update(kwargs) if kwargs.get("cfg"): LOGGER.info(f"cfg file passed. Overriding default params with {kwargs['cfg']}.") overrides = yaml_load(check_yaml(kwargs["cfg"]), append_filename=False) overrides["task"] = self.task overrides["mode"] = "train" if not overrides.get("data"): raise AttributeError("Dataset required but missing, i.e. pass 'data=coco128.yaml'") if overrides.get("resume"): overrides["resume"] = self.ckpt_path self.trainer = self.TrainerClass(overrides=overrides) # if not overrides.get("resume"): # manually set model only if not resuming # self.trainer.model = self.trainer.get_model(weights=self.model if self.ckpt else None, cfg=self.model.yaml) # self.model = self.trainer.model #下面一行代码在正常情况下需要开启 # self.trainer.model = self.model self.trainer.train() # update model and cfg after training if RANK in {0, -1}: self.model, _ = attempt_load_one_weight(str(self.trainer.best)) self.overrides = self.model.args 2.2 ultralytics/yolo/engine/trainer.py找到check_resume和resume_training方法 在check_resume方法里面将resume=中断地方的last.pt 在resume_training里面将ckpt=中断地方的last.pt def check_resume(self): # resume = self.args.resume resume = 'runs/detect/train49/weights/last.pt'; if resume: try: last = Path( check_file(resume) if isinstance(resume, (str, Path)) and Path(resume).exists() else get_latest_run()) self.args = get_cfg(attempt_load_weights(last).args) self.args.model, resume = str(last), True # reinstate except Exception as e: raise FileNotFoundError("Resume checkpoint not found. Please pass a valid checkpoint to resume from, " "i.e. 'yolo train resume model=path/to/last.pt'") from e self.resume = resume def resume_training(self, ckpt): ckpt = torch.load('runs/detect/train49/weights/last.pt') if ckpt is None: return best_fitness = 0.0 start_epoch = ckpt['epoch'] + 1 if ckpt['optimizer'] is not None: self.optimizer.load_state_dict(ckpt['optimizer']) # optimizer best_fitness = ckpt['best_fitness'] if self.ema and ckpt.get('ema'): self.ema.ema.load_state_dict(ckpt['ema'].float().state_dict()) # EMA self.ema.updates = ckpt['updates'] if self.resume: assert start_epoch > 0, \ f'{self.args.model} training to {self.epochs} epochs is finished, nothing to resume.\n' \ f"Start a new training without --resume, i.e. 'yolo task=... mode=train model={self.args.model}'" LOGGER.info( f'Resuming training from {self.args.model} from epoch {start_epoch + 1} to {self.epochs} total epochs') if self.epochs |
今日新闻 |
推荐新闻 |
| CopyRight 2018-2019 办公设备维修网 版权所有 豫ICP备15022753号-3 |